ArticleInternational journal of molecular sciences2024
Tear Proteomics in Children and Adolescents with Type 1 Diabetes: A Promising Approach to Biomarker Identification of Diabetes Pathogenesis and Complications.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Canine Tear Proteomics: A New Frontier in Veterinary Ophthalmology.Veterinary ophthalmology · 2026Review
- Exploring tear biomarkers with shotgun proteomics for retinoblastoma diagnosis: a pilot study.The journal of liquid biopsy · 2026Article
- High-performance proteomics reveals immune, epithelial, and vascular dysregulation underlying lacrimal fluid defects in patients with aniridia.BMC ophthalmology · 2026Article
- Evaluating the Impact of Two Different Diets on the Protein Profile of the Brain, Liver, and Intestine of the Barramundi.Proteomes · 2026Article
- Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.Frontiers in immunology · 2026Review
- Simple, Fast, and Reliable Analysis of Label-Free Proteomics Data With the Proteomics Eye (ProtE).Proteomics. Clinical applications · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The aim of the current study was to investigate the tear proteome in children and adolescents with type 1 diabetes (T1D) compared to healthy controls, and to identify differences in the tear proteome of children with T1D depending on different characteristics of the disease. Fifty-six children with T1D at least one year after diagnosis, aged 6-17 years old, and fifty-six healthy age- and sex-matched controls were enrolled in this cross-sectional study. The proteomic analysis was based on liquid chromatography tandem mass spectrometry (LC-MS/MS) enabling the identification and quantification of the protein content via Data-Independent Acquisition by Neural Networks (DIA-NN). Data are available via ProteomeXchange with the identifier PXD052994. In total, 3302 proteins were identified from tear samples. Two hundred thirty-nine tear proteins were differentially expressed in children with T1D compared to healthy controls. Most of them were involved in the immune response, tissue homeostasis and inflammation. The presence of diabetic ketoacidosis at diagnosis and the level of glycemic control of children with T1D influenced the tear proteome. Tear proteomics analysis revealed a different proteome pattern in children with T1D compared to healthy controls offering insights on deregulated biological processes underlying the pathogenesis of T1D. Differences within the T1D group could unravel biomarkers for early detection of long-term complications of T1D.
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Registered trials
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